docs: def probabilities(self, choosers, alternatives):
          """
          Returns alternative probabilties for each chooser segment as
          a dictionary keyed by segment name.
  
          Parameters
          ----------
          choosers : pandas.DataFrame
              Table describing the agents making choices, e.g. households.
              Must have a column matching the .segmentation_col attribute.
          alternatives : pandas.DataFrame
              Table describing the things from which agents are choosing.
  
          Returns
          -------
          probabilties : dict of pandas.Series
  
          """
          logger.debug(
              'start: calculate probabilities in LCM group {}'.format(self.name))
          probs = {}
  
          for name, df in self._iter_groups(choosers):
              probs[name] = self.models[name].probabilities(df, alternatives)
  
          logger.debug(
              'finish: calculate probabilities in LCM group {}'.format(
                  self.name))
          return probs